AI Data Annotator – Outlier (Remote)
Conducted evaluation of AI-generated responses for quality, accuracy, safety, and relevance against project instructions. Labeled and annotated dataset items according to provided guidelines while flagging factual inaccuracies and reasoning errors. Performed quality assurance reviews to ensure outputs met labeling standards and productivity targets. • LLM response evaluation and rating • Dataset annotation and labeling per guidelines • Error detection: factual inaccuracies and reasoning issues • QA review and guideline compliance checks